Decode Human Life from Social Media

In this big data era, people leave clues of their life consciously or unconsciously on many social media platforms in various forms. By mining data from social media, researchers can uncover the patterns of human life at both individual and group levels. Social media is one of the major data sources for such studies for mainly two reasons. 1) The huge volume and open access of data on these platforms, and 2) the diversity of data on different platforms, such as multimedia data on Twitter and Facebook, geolocation data on Foursquare and Yelp, as well as career data on Linkedin. In this paper, we introduce our work on studying human life based on social media data, and report the plan for our subsequent studies. Our work is intended to decodes human life from two perspectives. From a linguistic perspective, we study the language patterns of different social groups of people. The learned language patterns can reveal the specific characteristics of these groups, and provide novel angles to understanding people. From a mobility perspective, we extract the mobility patterns of individual person, and groups of people such as residents of certain regions. Using the detected mobility patterns, we mine knowledge of human life including the lifestyles and shopping patterns of cities and regions. We intend to combine these two perspectives in our ongoing work, and introduce a novel framework for study human life.